دانلود رایگان مقاله انگلیسی تحلیل هیدرولوژیکی با استفاده از سنجش از راه دور کلان داده و مدل CREST - نشریه IEEE 2018

ABSTRACT

Hydrological modelling significantly contributes to the understanding of catchment water balance and water resource management and mitigates negative impacts of flooding. Considering the advantages of satellite remote sensing big data and the Coupled Routing and Excess Storage (CREST) model, this paper investigates the hydrological modelling in the Shehong basin during 2006-2013. The results show that humid Shehong basin has main rainfalls in summer (From May to September). For the monthly average rainfall and streamflow, there is a remarkable increase (+52%) in discharge and a smaller increase (+18%) in rainfall in the second period (2010-2013) relative to the first period (2006-2009). The CREST model was calibrated using China Gauge-Based Daily Precipitation Analysis (CGDPA) for the period of 2006-2009, followed by a favorable performance with Nash-Sutcliffe coefficient efficiency (NSCE) of 0.77, correlation coefficient (CC) up to 0.88 and -11% Bias. The model validation shows an error metric with NSCE of 0.74, CC of 0.87 and -11.7% Bias. In terms of water balance modeling results at Shehong basin, the runoff and rainfall estimates from CREST model coincide well with the gauge observations, indicating the model captures the appropriate signature of soil moisture variability. Therefore, the satellite-based precipitation product is feasible in hydrological prediction, and the CREST models the interaction between surface and subsurface water flow process in the Shehong basin.

VII. CONCLUSIONS

The study investigates hydrological modelling in Shehong basin, a humid region in southwest China utilizing CREST model and satellite remote sensing big data. The rainfall and discharge observations show that the main rainfall of Shehong basin is concentrated in summer (May to September) because of subtropical humid monsoon climate. There is an overall remarkable increase (+52%) in discharge and relatively less increase (+18%) in rainfall. Gauged and simulated discharges agree well with each other during the calibration and validation periods, with the gauged precipitation and 3B42V7 as precipitation forcing. TMPA3B42V7 product shows comparable hydrologic utility with the reference precipitation in hydrological prediction at Shehong basin. Monthly model runoff estimates show considerable agreement with gauge observations recorded at Shehong station, indicating CREST model can capture the soil moisture storage variability. Change in storage patterns (the sum of change in storage is close to zero) indicate that CREST model reproduces the water cycle processes at Shehong basin with acceptable skills. In terms of water balance reconstruction results, the model is proven to be beneficial in addressing issues pertaining to sustainability of water resources within the catchment with respect to model robustness and effectiveness. Therefore, Satellite precipitation products help to understand the potential hydrological utility of remote sensing data for hydrological modelling studies in ungauged or poorly gauged basins. As retrospectively processed GPM-era IMERG datasets are released, more studies to simulate the key hydrological processes and reconstruct the water budget are required in the future.